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Macroeconomic Forecasting and Structural Change

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  • Antonello D'Agostino
  • Luca Gambetti
  • Domenico Giannone

Abstract

The aim of this paper is to assess whether explicitly modeling structural change increases the accuracy of macroeconomic forecasts. We produce real time out-of-sample forecasts for inflation, the unemployment rate and the interest rate using a Time-Varying Coe±cients VAR with Stochastic Volatility (TV-VAR) for the US. The model generates accurate predictions for the three variables. In particular for inflation the TV-VAR outperforms, in terms of mean square forecast error, all the competing models: fixed coefficients VARs, Time-Varying ARs and the naaive random walk model. These results are also shown to hold over the most recent period in which it has been hard to forecast inflation.

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Bibliographic Info

Paper provided by ULB -- Universite Libre de Bruxelles in its series Working Papers ECARES with number 2009_020.

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Length: 29 p.
Date of creation: 2009
Date of revision:
Publication status: Published by:
Handle: RePEc:eca:wpaper:2009_020

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Keywords: Forecasting; infation; stochastic Volatility; time varying vector autoregression.;

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